MNT: Modernize setup.py, beef up test workflow

.travis.yml

@@ -20,7 +20,10 @@ install:
   - cp test/matplotlibrc .
 
 script:
-  - nosetests --verbose --with-id --with-coverage --cover-package=metar
+  - cd ~
+  - source activate testenv
+  - python -c "import metar; metar.test()"
+  #- nosetests --verbose --with-id --with-coverage --cover-package=metar
 
 after_success:
   - coveralls

metar/station.py

@@ -6,11 +6,8 @@
 
 # std lib stuff
 import datetime
-from six.moves.urllib import request
-from six.moves.urllib import error
-from six.moves.urllib import parse
-from six.moves import http_cookiejar
 import os
+import sys
 import pdb
 import codecs
 
@@ -20,6 +17,12 @@
 import matplotlib.dates as mdates
 import pandas
 
+#compat
+from six.moves.urllib import request
+from six.moves.urllib import error
+from six.moves.urllib import parse
+from six.moves import http_cookiejar
+
 # metar stuff
 from . import metar
 from . import datatypes
@@ -49,13 +52,14 @@ class WeatherStation(object):
     """
 
     def __init__(self, sta_id, city=None, state=None, country=None,
-                 lat=None, lon=None, max_attempts=10):
+                 lat=None, lon=None, max_attempts=10, show_progress=False):
         self.sta_id = sta_id
         self.city = city
         self.state = state
         self.country = country
         self.position = datatypes.position(lat, lon)
-        self.max_attempts = max_attempts
+        self._max_attempts = max_attempts
+        self._show_progress = show_progress
 
         if self.state:
             self.name = "%s, %s" % (self.city, self.state)
@@ -69,6 +73,19 @@ def __init__(self, sta_id, city=None, state=None, country=None,
         self._wunder_nonairport = None
         self._asos = None
 
+    @property
+    def show_progress(self):
+        return self._show_progress
+    @show_progress.setter
+    def show_progress(self, value):
+        self._show_progress = value
+
+    @property
+    def max_attempts(self):
+        return self._max_attempts
+    @max_attempts.setter
+    def max_attempts(self, value):
+        self._max_attempts = value
 
     @property
     def wunderground(self):
@@ -430,7 +447,9 @@ def _get_data(self, startdate, enddate, source, filename):
         labelfxn = lambda ts, status: '{} {}: {}'.format(
             self.sta_id, ts.strftime('%Y.%m.%d'), status
         )
-        progress = metar.ProgressBar(timestamps, labelfxn=labelfxn)
+
+        if self.show_progress:
+            progress = metar.ProgressBar(timestamps, labelfxn=labelfxn)
 
         data = None
         for n, ts in enumerate(timestamps):
@@ -440,7 +459,8 @@ def _get_data(self, startdate, enddate, source, filename):
                 newdata, status = self._read_csv(ts, source)
                 data = data.append(newdata)
 
-            progress.animate(n+1, status)
+            if self.show_progress:
+                progress.animate(n+1, status)
 
         # add a row number to each row
         data['rownum'] = list(range(data.shape[0]))
@@ -715,16 +735,13 @@ def _process_sky_cover(obs):
 
 
 def getAllStations():
-    station_file_name = "reference/nsd_cccc.txt"
-    #station_file_url = "http://www.noaa.gov/nsd_cccc.txt"
+    stationfile = os.path.join(sys.prefix, 'metar_data', 'reference', 'nsd_cccc.txt')
     stations = {}
 
-    fh = open(station_file_name, 'r')
-    for line in fh:
-        f = line.strip().split(";")
-        stations[f[0]] = (f[0], f[3], f[4], f[5], f[7], f[8])
-
-    fh.close()
+    with open(stationfile, 'r') as fh:
+        for line in fh:
+            f = line.strip().split(";")
+            stations[f[0]] = (f[0], f[3], f[4], f[5], f[7], f[8])
 
     return stations
 

metar/tests/exporters_tests.py

@@ -1,21 +1,30 @@
+import os
+import sys
+
 import nose.tools as ntools
-from metar import station
-from metar import exporters
 import datetime as dt
 import pandas
 import matplotlib
 import matplotlib.pyplot as plt
 from six import StringIO
 
+from metar import station
+from metar import exporters
+
+
+@ntools.nottest
+def getTestFile(filename):
+    return os.path.join(sys.prefix, 'metar_data', 'test_data', filename)
+
 class test_exporter(object):
     def setup(self):
-        self.fivemin = pandas.read_csv('test/data_for_tests.csv',
+        self.fivemin = pandas.read_csv(getTestFile('data_for_tests.csv'),
                                        parse_dates=True, index_col=0)
         self.hourly = self.fivemin.resample('1H', how='sum')
 
-        self.known_fivemin_swmm5_file = 'test/known_fivemin_swmm5.dat'
-        self.known_hourly_swmm5_file = 'test/known_hourly_swmm5.dat'
-        self.knwon_hourly_ncdc_file = 'test/known_hourly_NCDC.dat'
+        self.known_fivemin_swmm5_file = getTestFile('known_fivemin_swmm5.dat')
+        self.known_hourly_swmm5_file = getTestFile('known_hourly_swmm5.dat')
+        self.knwon_hourly_ncdc_file = getTestFile('known_hourly_NCDC.dat')
 
         with open(self.known_fivemin_swmm5_file, 'r') as f:
             self.known_fivemin_swmm5 = f.read()
@@ -36,7 +45,7 @@ def test_dumpSWMM5Format_form(self):
             col='precip',
             freq='5min',
             dropzeros=True,
-            filename='test/test_dumpSWMM.dat'
+            filename=getTestFile('test_dumpSWMM.dat')
         )
         ntools.assert_true(isinstance(data, pandas.DataFrame))
         ntools.assert_list_equal(
@@ -51,7 +60,7 @@ def test_dumpSWMM5Format_DropZeros(self):
             col='precip',
             freq='5min',
             dropzeros=True,
-            filename='test/test_dumpSWMM_withoutZeros.dat'
+            filename=getTestFile('test_dumpSWMM_withoutZeros.dat')
         )
         ntools.assert_equal(data[data.precip == 0].shape[0], 0)
 
@@ -62,12 +71,12 @@ def test_dumpSWMM5Format_KeepZeros(self):
             col='precip',
             freq='5min',
             dropzeros=False,
-            filename='test/test_dumpSWMM_withZeros.dat'
+            filename=getTestFile('test_dumpSWMM_withZeros.dat')
         )
         ntools.assert_greater(data[data.precip == 0].shape[0], 0)
 
     def test_dumpSWMM5Format_Result5min(self):
-        testfilename = 'test/test_dumpSWMM_fivemin.dat'
+        testfilename = getTestFile('test_dumpSWMM_fivemin.dat')
         data = exporters.SWMM5Format(
             self.fivemin,
             'Test-Station',
@@ -85,7 +94,7 @@ def test_dumpSWMM5Format_Result5min(self):
         ntools.assert_equal(known_data, test_data)
 
     def test_dumpSWMM5Format_ResultHourly(self):
-        testfilename = 'test/test_dumpSWMM_hourly.dat'
+        testfilename = getTestFile('test_dumpSWMM_hourly.dat')
         data = exporters.SWMM5Format(
             self.fivemin,
             'Test-Station',
@@ -103,7 +112,7 @@ def test_dumpSWMM5Format_ResultHourly(self):
         ntools.assert_equal(known_data, test_data)
 
     def test_dumpNCDCFormat(self):
-        testfilename = 'test/test_dumpNCDCFormat.dat'
+        testfilename = getTestFile('test_dumpNCDCFormat.dat')
         data = exporters.NCDCFormat(
             self.hourly,
             '041685',

metar/tests/graphics_tests.py

@@ -1,55 +1,64 @@
-from nose.tools import *
-from metar import station
-from metar import graphics
+import os
+import sys
+
+import nose.tools as ntools
 import datetime as dt
 import pandas
 import matplotlib
 import matplotlib.pyplot as plt
+plt.rcParams['text.usetex'] = False
+
+from metar import station
+from metar import graphics
+
+@ntools.nottest
+def getTestFile(filename):
+    return os.path.join(sys.prefix, 'metar_data', 'test_data', filename)
 
 class test_graphics():
     def setup(self):
         self.freqlist = ['5min', 'hourly', 'daily', 'weekly']
-        self.df = pandas.read_csv('test/data_for_graphics_tests.csv',
+        self.df = pandas.read_csv(getTestFile('data_for_graphics_tests.csv'),
                                   parse_dates=True, index_col=0)
 
     def teardown(self):
         plt.close('all')
 
     def test_rainClock(self):
         '''Confirm that rainClock returns an mpl figure and two axes'''
-        fig = graphics.rainClock(self.df, fname='test/test_rainClock.png')
-        assert_true(isinstance(fig, matplotlib.figure.Figure))
+        fig = graphics.rainClock(self.df, fname=getTestFile('test_rainClock.png'))
+        ntools.assert_true(isinstance(fig, matplotlib.figure.Figure))
         pass
 
     def test_windRose_kt(self):
         '''Confirm that windRose returns an mpl figure and one axis'''
-        fig = graphics.windRose(self.df, fname='test/test_windRose_kt.png',
+        fig = graphics.windRose(self.df, fname=getTestFile('test_windRose_kt.png'),
                                 mph=False)
-        assert_true(isinstance(fig, matplotlib.figure.Figure))
+        ntools.assert_true(isinstance(fig, matplotlib.figure.Figure))
 
     def test_windRose_mph(self):
         '''Confirm that windRose returns an mpl figure and one axis'''
-        fig = graphics.windRose(self.df, fname='test/test_windRose_mph.png',
+        fig = graphics.windRose(self.df, fname=getTestFile('test_windRose_mph.png'),
                                 mph=True)
-        assert_true(isinstance(fig, matplotlib.figure.Figure))
+        ntools.assert_true(isinstance(fig, matplotlib.figure.Figure))
 
     def test_hyetograph(self):
         '''Confirm that hyetograph returns an mpl figure and one axis'''
         for freq in self.freqlist:
-            fname = 'test/test_hyetograph_%s.png' % freq
+            fname = getTestFile('test_hyetograph_%s.png' % freq)
             fig = graphics.hyetograph(self.df, freq=freq, fname=fname)
-            assert_true(isinstance(fig, matplotlib.figure.Figure))
+            ntools.assert_true(isinstance(fig, matplotlib.figure.Figure))
 
     def test_psychromograph(self):
         '''Confirm that psychromograph returns an mpl figure and one axis'''
         for freq in self.freqlist:
-            fname = 'test/test_psychromograph_%s.png' % freq
+            fname = getTestFile('test_psychromograph_%s.png' % freq)
             fig = graphics.psychromograph(self.df, freq=freq, fname=fname)
-            assert_true(isinstance(fig, matplotlib.figure.Figure))
+            ntools.assert_true(isinstance(fig, matplotlib.figure.Figure))
 
     def test_temperaturePlot(self):
         '''Confirm that temperaturePlot returns an mpl figure and one axis'''
         for freq in self.freqlist:
-            fname = 'test/test_temperaturePlot_%s.png' % freq
+            fname = getTestFile('test_temperaturePlot_%s.png' % freq)
             fig = graphics.temperaturePlot(self.df, freq=freq, fname=fname)
-            assert_true(isinstance(fig, matplotlib.figure.Figure))
+            ntools.assert_true(isinstance(fig, matplotlib.figure.Figure))

metar/tests/stations_tests.py

@@ -1,6 +1,7 @@
 import shutil
 import datetime as dt
 import os
+import sys
 
 import nose.tools as ntools
 import numpy as np
@@ -11,10 +12,12 @@
 from metar import station
 from metar import metar
 
+@ntools.nottest
 class fakeClass(object):
     def value(self):
         return 'item2'
 
+@ntools.nottest
 def makeFakeRainData():
     tdelta = dt.datetime(2001, 1, 1, 1, 5) - dt.datetime(2001, 1, 1, 1, 0)
     start = dt.datetime(2001, 1, 1, 12, 0)
@@ -32,6 +35,11 @@ def makeFakeRainData():
     return daterange, rain_raw
 
 
+@ntools.nottest
+def getTestFile(filename):
+    return os.path.join(sys.prefix, 'metar_data', 'test_data', filename)
+
+
 class test_station():
     def setup(self):
         self.max_attempts = 3
@@ -225,9 +233,10 @@ def test_check_step(self):
         ntools.assert_raises(ValueError, station._check_step, 'fart')
 
     def test_check_file(self):
-        ntools.assert_equal(station._check_file('test/testfile1'), 'bad')
-        ntools.assert_equal(station._check_file('test/testfile2'), 'ok')
-        ntools.assert_equal(station._check_file('test/testfile3'), 'not there')
+        known_results = ['bad', 'ok', 'not there']
+        for n, known_result in enumerate(known_results, 1):
+            fn = getTestFile('testfile{:d}'.format(n))
+            ntools.assert_equal(station._check_file(fn), known_result)
 
     def test_check_dirs(self):
         pass